P1533: A PROGNOSTIC MODEL FOR PATIENTS WITH SEPTIC SHOCK AFTER ALLOGENEIC HEMATOPOIETIC STEM CELL TRANSPLANTATION
Authors: Qiu-Sha Huang, Tian-Xiao Han, Xiao-Lu Zhu, Hai-Xia Fu, Yun He, Feng-Rong Wang, Yuan-Yuan Zhang, Xiao-Dong Mo, Wei Han, Jing-Zhi Wang, Yu Wang, Huan Chen, Yu-Hong Chen, Chen-Hua Yan, Yuan Kong, Xiang-Yu Zhao, Ying-Jun Chang, Lan-Ping Xu, Kai-Yan Liu, Xiao-Jun Huang, Xiao-Hui Zhang
Journal: HemaSphere (2023)

Topic: 30. Infections in hematology (incl. supportive care/therapy) Background: Allogeneic hematopoietic stem cell transplantation (allo-HSCT) is a promising therapeutic option for various malignant and non-malignant hematologic diseases. Nonetheless, patients undergoing allo-HSCT are at a particularly higher risk for infectious complications that could lead to septic shock and associated morbidity and mortality. Septic shock remains a potentially fatal complication among HSCT recipients. The existing clinical sepsis tools have limited prognostic value for this high-risk population. Aims: We aimed to develop and validate a new scoring system for predicting death within 28 days of septic shock onset in patients who underwent allogeneic hematopoietic stem cell transplantation. Methods: We retrospectively studied 278 septic shock patients from 6105 consecutive patients who were allografted between 2007 and 2020. The derivation cohort included 195 patients who received allo-HSCT from 2007 to 2017. For the external validation cohort, we included 83 patients who received allo-HSCT from 2018 to 2020. We assessed 27 risk factors as candidate predictors and used multivariable logistic regression to develop our prediction model. An easy-to-use risk score system was developed, and its performance was compared with that of the existing clinical sepsis tool Sequential Organ Failure Assessment (SOFA) using internal and external validation cohorts. Results: A total of 55.4% (108/195) of patients in the derivation cohort and 38.6% (32/83) in the validation cohort died within 28 days of septic shock diagnosis. The overall 28-day mortality was 50.4% (140/278), with 65 (23.4%) patients hospitalized in the ICU. A total of 82.9% of deaths (116/140) occurred within the first 7 days. In this study, we analysed patients with septic shock in two distinct cohorts: early-onset shock (patients admitted for engraftment) and late-onset shock (patients admitted after engraftment). The median time from HSCT to septic shock was 8 (0-11) days in the early-onset shock cohort and 208 (81-444) days in the late-onset shock cohort. Patients with late-onset shock had higher 28-day mortality than those with early-onset shock (65.9% vs. 24.8%, P <0.001). A total of 172 patients (61.9%) had positive blood cultures. Gram-negative bacilli accounted for 61.0% of the positive isolates, gram-positive cocci accounted for 10.5%, and fungi accounted for 5.8%. Escherichia coli was the dominant isolated pathogen (31.4%), followed by Pseudomonas spp. (12.2%) and Klebsiella pneumoniae (9.9%). The final model included five variables and was named T-ABCL (time of septic shock, albumin, bilirubin, C-reactive protein and lactate). An easy-to-use risk score system was developed, and its performance was compared with that of the existing clinical sepsis tool Sequential Organ Failure Assessment (SOFA) using internal and external validation cohorts. The T-ABCL model had an AUC of 0.889 (95% CI 0.790-0.964) in internal validation and 0.874 (95% CI 0.787-0.961) in external validation, which is superior to that of the SOFA score (0.707 (95% CI 0.580-0.834), P = 0.002). The calibration plots demonstrated good consistency between the T-ABCL model-predicted and observed outcomes in both internal validation and external validation. Summary/Conclusion: We developed and validated a highly accurate prediction model for 28-day mortality of septic shock after allogeneic hematopoietic stem cell transplantation. It has the potential to guide tailored therapy and is a step towards more personalized medicine.Keywords: Sepsis, Survival prediction, Allogeneic hematopoietic stem cell transplant